data/coco128.yaml, shown below, is the dataset config file that defines 1) the dataset root directory path and relative paths to train / val / test image directories (or *.txt files with image paths) and 2) a class names dictionary: # Train/val/test sets as 1) dir: path/to/imgs,...
args = dict(model='yolov8n.pt', data='coco8.yaml', epochs=3) trainer = DetectionTrainer(overrides=args) trainer.train() ``` """ def build_dataset(self, img_path, mode="train", batch=None): """ Build YOLO Dataset. Args: img_path (str): Path to the folder containing...
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if isinstance(self.args.data, str) and self.args.data.endswith('.yaml'): self.data = check_det_dataset(self.args.data) elif self.args.task == 'classify': self.data = check_cls_dataset(self.args.data) else: raise FileNotFoundError(emojis(f"Dataset '{self.args.data}' for task={se...
{p} does not exist") self.img_files = sorted([x.replace("/", os.sep) for x in f if x.split(".")[-1].lower() in self.img_formats]) assert self.img_files, f"No images found" except Exception as e: raise Exception(f"Error loading data from {self.path}: {e}\n") # ...
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